{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "880cc845",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/vector_stores/WeaviateIndexDemo-Hybrid.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "307804a3-c02b-4a57-ac0d-172c30ddc851",
   "metadata": {},
   "source": [
    "# Weaviate Vector Store - Hybrid Search"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "1a07d618",
   "metadata": {},
   "source": [
    "If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fd9a64d",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install llama-index-vector-stores-weaviate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c39b4adf",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install llama-index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eccceb71",
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "import sys\n",
    "\n",
    "logging.basicConfig(stream=sys.stdout, level=logging.INFO)\n",
    "logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7010b1d-d1bb-4f08-9309-a328bb4ea396",
   "metadata": {},
   "source": [
    "## Creating a Weaviate Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ac755d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import openai\n",
    "\n",
    "os.environ[\"OPENAI_API_KEY\"] = \"\"\n",
    "openai.api_key = os.environ[\"OPENAI_API_KEY\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "72a4b618-668d-4713-84c5-6362030e9f19",
   "metadata": {},
   "outputs": [],
   "source": [
    "import weaviate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de43b464",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Connect to cloud instance\n",
    "cluster_url = \"\"\n",
    "api_key = \"\"\n",
    "\n",
    "client = weaviate.connect_to_wcs(\n",
    "    cluster_url=cluster_url,\n",
    "    auth_credentials=weaviate.auth.AuthApiKey(api_key),\n",
    ")\n",
    "\n",
    "# Connect to local instance\n",
    "# client = weaviate.connect_to_local()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a2bcc07",
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core import VectorStoreIndex, SimpleDirectoryReader\n",
    "from llama_index.vector_stores.weaviate import WeaviateVectorStore\n",
    "from llama_index.core.response.notebook_utils import display_response"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "382ce1d4",
   "metadata": {},
   "source": [
    "## Download Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb0680fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "!mkdir -p 'data/paul_graham/'\n",
    "!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ee4473a-094f-4d0a-a825-e1213db07240",
   "metadata": {},
   "source": [
    "## Load documents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68cbd239-880e-41a3-98d8-dbb3fab55431",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load documents\n",
    "documents = SimpleDirectoryReader(\"./data/paul_graham/\").load_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17fbf703",
   "metadata": {},
   "source": [
    "## Build the VectorStoreIndex with WeaviateVectorStore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba1558b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core import StorageContext\n",
    "\n",
    "\n",
    "vector_store = WeaviateVectorStore(weaviate_client=client)\n",
    "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n",
    "index = VectorStoreIndex.from_documents(\n",
    "    documents, storage_context=storage_context\n",
    ")\n",
    "\n",
    "# NOTE: you may also choose to define a index_name manually.\n",
    "# index_name = \"test_prefix\"\n",
    "# vector_store = WeaviateVectorStore(weaviate_client=client, index_name=index_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "622599aa",
   "metadata": {},
   "source": [
    "## Query Index with Default Vector Search"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82f154f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set Logging to DEBUG for more detailed outputs\n",
    "query_engine = index.as_query_engine(similarity_top_k=2)\n",
    "response = query_engine.query(\"What did the author do growing up?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2c5bd359",
   "metadata": {},
   "outputs": [],
   "source": [
    "display_response(response)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04304299-fc3e-40a0-8600-f50c3292767e",
   "metadata": {},
   "source": [
    "## Query Index with Hybrid Search"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4925c9e6",
   "metadata": {},
   "source": [
    "Use hybrid search with bm25 and vector.  \n",
    "`alpha` parameter determines weighting (alpha = 0 -> bm25, alpha=1 -> vector search).  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93e9f4d6",
   "metadata": {},
   "source": [
    "### By default, `alpha=0.75` is used (very similar to vector search)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35369eda",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set Logging to DEBUG for more detailed outputs\n",
    "query_engine = index.as_query_engine(\n",
    "    vector_store_query_mode=\"hybrid\", similarity_top_k=2\n",
    ")\n",
    "response = query_engine.query(\n",
    "    \"What did the author do growing up?\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bedbb693-725f-478f-be26-fa7180ea38b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "display_response(response)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80396381",
   "metadata": {},
   "source": [
    "### Set `alpha=0.` to favor bm25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b4b26d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set Logging to DEBUG for more detailed outputs\n",
    "query_engine = index.as_query_engine(\n",
    "    vector_store_query_mode=\"hybrid\", similarity_top_k=2, alpha=0.0\n",
    ")\n",
    "response = query_engine.query(\n",
    "    \"What did the author do growing up?\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d755768",
   "metadata": {},
   "outputs": [],
   "source": [
    "display_response(response)"
   ]
  }
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